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NVIDIA BioNeMo is a framework for training and deploying large biomolecular language models
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at the supercomputing scale. The large language model (LLM) framework will support chemistry, protein, DNA and RNA data formats, which aims to help scientists better understand disease and find therapies for patients.
This would be a part of the NVIDIA Clara Discovery applications, collection of frameworks, and AI models for drug discovery. As AI is learning to understand human languages with LLMs, it’s also learning the languages of chemistry and biology. The framework would make it easier to train massive neural networks on biomolecular data and help researchers discover new patterns and insights in biological sequences. With these fresh insights, researchers can connect to biological functions, including human health conditions.
“As we see the ever-widening adoption of large language models in the protein space, being
able to efficiently train LLMs and quickly modulate model architectures is becoming hugely
important,” said Istvan Redl, machine learning lead at Peptone, a biotech startup in the NVIDIA
Inception program. “We believe that these two engineering aspects—scalability and rapid
experimentation—are exactly what the BioNeMo framework could provide.”
The framework will be available in early access on NVIDIA GPU Cloud, a hub for GPU-optimised software. A wave of experts in biotech and pharma such as AstraZeneca, OpenFold, Peptone, and Evozyne, including researchers at the Broad Institute of MIT and Harvard are adopting NVIDIA BioNeMo to support drug discovery research.